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Patrick Stalph (18 results)
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Analysis and Design of Machine Learning Techniques: Evolutionary Solutions for Regression, Prediction, and Control Problems
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
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Analysis and Design of Machine Learning Techniques : Evolutionary Solutions for Regression, Prediction, and Control Problems
Language: English
Published by Springer Vieweg 2014-02, 2014
ISBN 10: 3658049367 ISBN 13: 9783658049362
US$ 66.27
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Analysis and Design of Machine Learning Techniques : Evolutionary Solutions for Regression, Prediction, and Control Problems
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
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Condition: New. pp. 176.
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Analysis and Design of Machine Learning Techniques: Evolutionary Solutions for Regression, Prediction, and Control Problems
Language: English
Published by Vieweg + Teubner Verlag, 2014
ISBN 10: 3658049367 ISBN 13: 9783658049362
US$ 88.33
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Add to basketPaperback. Condition: Brand New. 2014 edition. 188 pages. 8.25x5.75x0.50 inches. In Stock.
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Analysis and Design of Machine Learning Techniques : Evolutionary Solutions for Regression, Prediction, and Control Problems
Language: English
Published by Springer Fachmedien Wiesbaden, 2014
ISBN 10: 3658049367 ISBN 13: 9783658049362
Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Manipulating or grasping objects seems like a trivial task for humans, as these are motor skills of everyday life. Nevertheless, motor skills are not easy to learn for humans and this is also an active research topic in robotics. However, most solutions are optimized for industrial applications and, thus, few are plausible explanations for human learning. The fundamental challenge, that motivates Patrick Stalph, originates from the cognitive science: How do humans learn their motor skills The author makes a connection between robotics and cognitive sciences by analyzing motor skill learning using implementations that could be found in the human brain - at least to some extent. Therefore three suitable machine learning algorithms are selected - algorithms that are plausible from a cognitive viewpoint and feasible for the roboticist. The power and scalability of those algorithms is evaluated in theoretical simulations and more realistic scenarios with the iCub humanoid robot. Convincing results confirm the applicability of the approach, while the biological plausibility is discussed in retrospect.
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Analysis and Design of Machine Learning Techniques : Evolutionary Solutions for Regression, Prediction, and Control Problems
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
US$ 127.05
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Analysis and Design of Machine Learning Techniques | Evolutionary Solutions for Regression, Prediction, and Control Problems
Language: English
Published by Springer Fachmedien Wiesbaden, 2014
ISBN 10: 3658049367 ISBN 13: 9783658049362
Taschenbuch. Condition: Neu. Analysis and Design of Machine Learning Techniques | Evolutionary Solutions for Regression, Prediction, and Control Problems | Patrick Stalph | Taschenbuch | xix | Englisch | 2014 | Springer Fachmedien Wiesbaden | EAN 9783658049362 | Verantwortliche Person für die EU: Springer Vieweg in Springer Science + Business Media, Abraham-Lincoln-Str. 46, 65189 Wiesbaden, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
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Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Manipulating or grasping objects seems like a trivial task for humans, as these are motor skills of everyday life. Nevertheless, motor skills are not easy to learn for humans and this is also an active research topic in robotics. However, most solutions are optimized for industrial applications and, thus, few are plausible explanations for human learning. The fundamental challenge, that motivates Patrick Stalph, originates from the cognitive science: How do humans learn their motor skills? The author makes a connection between robotics and cognitive sciences by analyzing motor skill learning using implementations that could be found in the human brain ¿ at least to some extent. Therefore three suitable machine learning algorithms are selected ¿ algorithms that are plausible from a cognitive viewpoint and feasible for the roboticist. The power and scalability of those algorithms is evaluated in theoretical simulations and more realistic scenarios with the iCub humanoid robot. Convincing results confirm the applicability of the approach, while the biological plausibility is discussed in retrospect.
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Condition: new. Questo è un articolo print on demand.
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Analysis and Design of Machine Learning Techniques
Language: English
Published by Springer Fachmedien Wiesbaden Feb 2014, 2014
ISBN 10: 3658049367 ISBN 13: 9783658049362
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Manipulating or grasping objects seems like a trivial task for humans, as these are motor skills of everyday life. Nevertheless, motor skills are not easy to learn for humans and this is also an active research topic in robotics. However, most solutions are optimized for industrial applications and, thus, few are plausible explanations for human learning. The fundamental challenge, that motivates Patrick Stalph, originates from the cognitive science: How do humans learn their motor skills The author makes a connection between robotics and cognitive sciences by analyzing motor skill learning using implementations that could be found in the human brain - at least to some extent. Therefore three suitable machine learning algorithms are selected - algorithms that are plausible from a cognitive viewpoint and feasible for the roboticist. The power and scalability of those algorithms is evaluated in theoretical simulations and more realistic scenarios with the iCub humanoid robot. Convincing results confirm the applicability of the approach, while the biological plausibility is discussed in retrospect. 176 pp. Englisch.
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Condition: New. Print on Demand pp. 176 62 Illus.
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Condition: New. PRINT ON DEMAND pp. 176.
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Analysis and Design of Machine Learning Techniques
Language: English
Published by Springer Fachmedien Wiesbaden, 2014
ISBN 10: 3658049367 ISBN 13: 9783658049362
Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Publication in the field of technical sciencesIntroduction and Motivation.- Introduction to Function Approximation and Regression.- Elementary Features of Local Learning Algorithms.- Algorithmic Description of XCSF.- How and Why XCSF works.- Evolutionar.
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Analysis and Design of Machine Learning Techniques
Language: English
Published by Springer Fachmedien Wiesbaden Feb 2014, 2014
ISBN 10: 3658049367 ISBN 13: 9783658049362
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germany
Seller rating 5 out of 5 stars
Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Manipulating or grasping objects seems like a trivial task for humans, as these are motor skills of everyday life. Nevertheless, motor skills are not easy to learn for humans and this is also an active research topic in robotics. However, most solutions are optimized for industrial applications and, thus, few are plausible explanations for human learning. The fundamental challenge, that motivates Patrick Stalph, originates from the cognitive science: How do humans learn their motor skills The author makes a connection between robotics and cognitive sciences by analyzing motor skill learning using implementations that could be found in the human brain ¿ at least to some extent. Therefore three suitable machine learning algorithms are selected ¿ algorithms that are plausible from a cognitive viewpoint and feasible for the roboticist. The power and scalability of those algorithms is evaluated in theoretical simulations and more realistic scenarios with the iCub humanoid robot. Convincing results confirm the applicability of the approach, while the biological plausibility is discussed in retrospect.Springer-Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 176 pp. Englisch.
